class_docstr: Base class for implementing dataset builders. See more information
  on top. Child class needs to implement ``build`` and ``load``.
  
  Args:
      dataset_name (str): Name of the dataset passed from child.
code: def build_dataloader(
      self,
      dataset_instance: Optional[Dataset],
      dataset_type: str,
      *args,
      **kwargs,
  ):
      if dataset_instance is None:
          raise TypeError(
              f"dataset instance for {dataset_type} hasn't been set and is None"
          )
      dataset_instance.dataset_type = dataset_type
      dataloader, _ = build_dataloader_and_sampler(
          dataset_instance, self.config
      )
      return dataloader
  
imports: import uuid
  from typing import Optional
  import pytorch_lightning
  from mmf.utils.build import build_dataloader_and_sampler
  from mmf.utils.logger import log_class_usage
  from omegaconf import DictConfig
  from torch.utils.data import Dataset
label_desc: Use image node_id 17 for calling the BaseDatasetBuilder obj's underlying member method code with example usage: obj.build_dataloader(dataset_instance, dataset_type) and returns: dataloader